J
Jung Uk Cho
Researcher at Samsung
Publications - 55
Citations - 1061
Jung Uk Cho is an academic researcher from Samsung. The author has contributed to research in topics: Image processing & Field-programmable gate array. The author has an hindex of 13, co-authored 55 publications receiving 1031 citations. Previous affiliations of Jung Uk Cho include Sungkyunkwan University & University of California, Los Angeles.
Papers
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Journal ArticleDOI
FPGA Design and Implementation of a Real-Time Stereo Vision System
Seunghun Jin,Jung Uk Cho,Xuan Dai Pham,Kyoung Mu Lee,Sung-Kee Park,Munsang Kim,Jae Wook Jeon +6 more
TL;DR: A fully pipelined stereo vision system providing a dense disparity image with additional sub-pixel accuracy in real-time in a single field programmable gate array (FPGA) without the necessity of any external devices is proposed.
Proceedings ArticleDOI
Fpga-based face detection system using Haar classifiers
TL;DR: The hardware design techniques including image scaling, integral image generation, pipelined processing as well as classifier, and parallel processing multiple classifiers to accelerate the processing speed of the face detection system are described.
Journal ArticleDOI
An FPGA-Based Multiple-Axis Motion Control Chip
TL;DR: This paper presents the design and implementation of a multiple-axis motion control chip using a field-programmable gate array (FPGA) designed to control a Multipleaxis motion system such as a robotic arm manipulator or a computer numerical control machine.
Proceedings ArticleDOI
A Real-Time Object Tracking System Using a Particle Filter
TL;DR: In order to track moving objects in real-time without delay and loss of image sequences, a particle filter algorithm specifically designed for a circuit and the circuit of the object tracking algorithm using the particle filter are proposed.
Proceedings ArticleDOI
Parallelized Architecture of Multiple Classifiers for Face Detection
TL;DR: The proposed parallelized architecture of multiple classifiers for face detection based on the Viola and Jones object detection method makes use of the AdaBoost algorithm which identifies a sequence of Haar classifiers that indicate the presence of a face.